Affiliations: [a] School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, China
| [b] Fujian Key Laboratory of Granular Computing and Applications, Minnan Normal University, Zhangzhou, P.R. China
Note: [1] This work is supported by the Key Program of the Natural Science Foundation of Fujian Province (No: 2020J02043) and the National Natural Science Foundation of China (Grant No. 11571158).
Abstract: The theory of knowledge spaces (KST) which is regarded as a mathematical framework for the assessment of knowledge and advices for further learning. Now the theory of knowledge spaces has many applications in education. From the topological point of view, we discuss the language of the theory of knowledge spaces by the axioms of separation and the accumulation points of pre-topology respectively, which establishes some relations between topological spaces and knowledge spaces; in particular, we show that the language of the regularity of pre-topology in knowledge spaces and give a characterization for knowledge spaces by inner fringe of knowledge states. Moreover, we study the relations of Alexandroff spaces and quasi ordinal spaces; then we give an application of the density of pre-topological spaces in primary items for knowledge spaces, which shows that one person in order to master an item, she or he must master some necessary items. In particular, we give a characterization of a skill multimap such that the delineated knowledge structure is a knowledge space, which gives an answer to a problem in [14] or [18] whenever each item with finitely many competencies; further, we give an algorithm to find the set of atom primary items for any finite knowledge space.
